About the job
Introduction
BlockTal is Partnered with a VC-backed startup revolutionizing enterprise security with cutting-edge generative AI technology. This role offers the chance to join their founding engineering team as a pivotal contributor, driving the design of scalable architectures and making key technical decisions that will shape the future of their platform.
What You'll Do:
- Lead the design and development of innovative features using LLMs
- Shape the architecture of their LLM solutions, making strategic decisions on model configurability, portability, and cost
- Stay at the forefront of LLM research, identifying groundbreaking techniques and tools to enhance their product offerings
- Hone your expertise in prompt engineering, fine-tuning, and in-context learning to unlock the full potential of LLMs and drive innovation within their product
Does this sound like you?
- 5+ Years of experience with a proven track record of shipping LLM-powered products or features
- Extensive expertise in large language models (LLMs), including fine-tuning, prompt engineering, model evaluation, and implementing safety protocols. Highly skilled in Python programming
- Proven experience in designing and scaling machine learning systems, with a strong focus on enhancing performance and optimizing resource efficiency
- Experience with Retrieval-Augmented Generation (RAG) or related methodologies for enhancing model performance and contextual accuracy
- Understanding of agent-based system design and the application of LLMs in enabling intelligent, autonomous agent architectures
Can't wait to hear more about this position? Click Apply below and reach out to Jeremy (...@blocktal.com) and they will be more than happy to share more details.
BlockTal & Code Red Partners are extremely committed to working with equal opportunity employers helping build a diverse and inclusive workforce within Cyber Security. We put the people we work with at the heart of everything we do and dedicate all we do to playing a part in developing an industry that represents a variety of backgrounds, perspectives, and skills.